*3.3. Assessment of the Optimization Scenarios from the View of Spatial Configuration: High Levels of Development Will Lead to Further Expansion of Industrial Production Space and Living Space*

The land area of PLE space in 2030 under different scenarios and the changes in terms of percentage compared with 2018 are listed in Table 8. Under the base scenario, urban living space (LU) is approximately 1.2 times larger than that in 2018, while rural living space (LR) decreases by approximately one-third (33.32%). The production land-use area shrinks from 6000.09 to 5760.48 km2, a decrease of approximately 4%, and priority agricultural production space and general agricultural production space shrink by 5.91%, while industrial production space grows by 3.8 times. This implies that the expansion of urban living space and industrial production space is very evident in the base scenario, while priority agricultural production space and industrial production space are the most occupied.

Under Scenario A1, because of the protection of agricultural production space, the expansion of living space and industrial production space leads to different degrees of reduction in ecological space. Ecological space decreases by 1.49%, industrial production space and urban living space increase by 241.56% and 194.98%, and rural living space increases by 3.7%. Under Scenario B1, there is a slight decrease in ecological space (approximately 0.01%). The expansion of living space and industrial production space is at the expense of agricultural production space, resulting in a 3.66% decrease. Compared with Scenario B1, the priority agricultural production space is protected with constraints in Scenario C1, leading to the general agricultural production space being further reduced by 7.93%.


**Table 8.** Land area of the PLE spaces in 2030 and changes compared with 2018 under different scenarios.

*3.4. Optimization Pattern of the Coordinated Development: Production–Living Space Should Be Given Priority*

The spatial optimization efficiency is evaluated by whether the spatial allocation can reach the future total amount required. When the FLUS model is used for the spatial layout, the number of requirements may not be reached for the same 600 iterations due to the different constraint rules. The percentage difference between the actual number of configurations and the demands is used as the spatial optimization efficiency indicator.

The future demand area of different land types needs to be proportionally converted to the number of land parcels in the FLUS model for spatial simulation. The gap between the actual allocation of parcels and the demand parcels is also presented in Table S19. In the base scenario, the expansion of rural living space far exceeds the planned demand by approximately 38%. In contrast, the number of allocated parcels of industrial production space differs from the number of demands by −22.63%, which means that it does not meet the target. In Scenario A1, 25.37% of the urban living space does not meet the future demand in the spatial configuration. In Scenario B1, neither urban living space nor industrial production space meets future needs; for example, the gap in urban living space is −22.14%. This is more obvious in Scenario C1, where 55.23% of the urban living space does not meet the demand.

Since the differences in several scenarios are mainly reflected in urban living space and industrial production space, the central and eastern regions are compared in separate enlargements (see Figure 8). Compared with 2018, the expansion of urban living space in the base scenario is mainly in the central region, centering on the original urban living space and expanding further outward. The expansion of industrial production space is also distributed in the central part but in a scattered manner around the central city, with the exception of two concentrated locations in the eastern region (see Figure 8).

Unlike the base scenario, the urban living space expands to the southwest with a small-scale agglomeration in Scenario A, and the same phenomenon occurs in the eastern part. In contrast, the expansion of industrial production space tends to extend to the south compared to the base scenario. The expansion of urban living space is very similar at different levels under Scenario B. Only Scenario B1 shows a clustering distribution in the northern part of the original urban living space and a relatively smaller degree of clustering in the eastern part. However, the industrial production space is not obvious in other scenarios except for a more obvious expansion at B1, especially in the northeastern region. In Scenario C, the expansion of urban living space and industrial production space is somewhat limited and only slightly expands compared to 2018, again mainly in the central and eastern regions.

(**a**)

**Figure 8.** *Cont.*

(**b**)

**Figure 8.** Spatial distribution of PLE space in different scenarios: (**a**) represent eastern region; (**b**) represent central region. And A1–C3 represent differen scenarios.
